How to Hack PR. A step by step guide for data driven startups.
Part 1: Who you should be working with, where should you be covered and what you should be saying.
Despite all the hype around platforms, growth hacking and viral co-efficients, one of the best levers marketers have is still PR.
Done well, it can be a highly cost-effective way to drive massive reach. But the problem is that it’s not predictable (you can’t count on it), attribution is a pain and you generally need an awesome story, the right connections (or an amazing agency) and alot of luck.
This hack isn’t a magic bullet, but helps give your PR campaign the best chance for success.
Our main goal is to drive sales by influencing the influencer. We have our target persona (the “influencer” or buyer. In large B2B sales it’s helpful to think of our main client advocate as an influencer, ie they still need to get buy in from their peers) and we shape what influences them by working the media that they consume.
We want to surround our target with positive stories that show us in a good light, but we want those stories to come with the credibility of third party media, rather than from our own self serving website or sales collateral.
Here’s how to get started.
- Identify a story angle that you know will get traction with the journalists that you want, at the publications that matter for you.
1: Map the circles of influence
I’m currently interested in hacking PR for a HR Tech firm, so the audience is senior HR buyers.
Firstly, come up all the things (people, media, blogs etc) that might influence how our target thinks about our topic of choice (in this case HR Tech). In my case, I have:
Consumer press: The most popular mass media newspapers in your country.
- Sydney Morning Herald
- The Australian
General business press: Mass media for business people.
- Australian Financial Review (AFR)
Specialist press: Trade rags. Blogs, magazines and websites dedicated to specific industries. Normally full of industry news, relevant events and interviews with industry leaders.
- HR Daily
- HR Mag
Their mates: What we really want is to be a fly on the wall when our target meets their work friends and talk shop. Obviously, that’s a little tricky, so we’ll use social shares as a proxy. I’m using BuzzSumo, but there are loads of tools you can use for “social media listening”.
Aggregators: Nowadays people tend to consume alot of media via news aggregators, such as Google or Linkedin and Facebook news feeds.
- Google News
2. Collect relevant stories
Now we’re going to go through each of those sources and collect, then analyse their relevant articles.
Firstly, go to the source and use their search function to search for your target topic. Don’t worry if your target site hides its content behind a paywall (like this example here) as all we need is the title and description — not the full article.
Next, we’ll scrape the results using an off the shelf web scraping tool called Data Miner. It’s a Chrome extension and it’s really easy to use, especially on structured data such as tables or (awesomely) search results pages.
Dataminer exports data as spreadsheets, so you need to define what data you want to include.
- Choose the rows you want. Go the 2nd tab and select a unit that is large enough to include all relevant parts of that story. I selected the boxes in green.
- Select the columns you want. Go the 3rd tab and choose data within each of the green boxes and label them separately. I’ve selected Heading, Date and Description. It can be a bit fiddling to get this working, so you might need to play around with the “Selector” options.
- Automate pagination. Click on the 4th tab in Dataminer and select “next” or “next page”. This tells the software to continue to the next SERPs page once it’s finished scraping one page.
And here’s the output:
Bonus! See what else you can grab
If you’re a lucky ducky, you will occasionally come across sites that not only tell you all their stories, but also how popular they are!
In this example from Forbes, you can see the number of views for each of their stories.
Notice though, that their top stories are all at least a year old. That makes sense — the longer it’s been published, the more time it’s had to accrue views.
So to get any meaningful insights, we need to standardise the data.
- Calculate the number of days each article has been live. Just find the number of today’s date, and subtract the number of the day it was published. You can use =today()-XX, where XX = the cell reference for the published date.
- Divide the number of total views by the number of days it’s been live.
- Voila! You now have an apples to apples comparison for story popularity. If you order largest to smallest by Views / Day, you’ll get vastly different (and more useful) results compared simply ordering by Views.
As an aside, using Conditional formatting (like the red and green bars highlighting the biggest numbers in the screenshot above) is a really awesome way of processing data quickly, especially if you’re a visual person.
Here’s the exact same process applied to BuzzSumo. BuzzSumo tells us how many shares an article has had in aggregate on the various platforms (see the right hand side columns. I’ve simply calculated days live and then Shares per Day.
If it’s available, you should also collect author name, categories, tags and the number of likes or comments.
3. Define your master categories
Now, we’re going to categorise stories to work out the key themes.
- Take the top five to ten stories from each of your sources. If you don’t have any data on articles views, just take the latest ten.
- Pop them on a blank canvas. I used OneNote, but you can use anything that lets you easily move words around on a page (eg Powerpoint, post it notes or a white board).
- Cluster them. Group thematically similar titles (see the black text below). You can see immediately in the pic below that there are lots of articles discussing “implementation”.
- Identify themes. Try and distill the common theme between all those grouped articles (see red text below). Keep working on the themes until you have a set that is collectively exhaustive and mutually exclusive (ie, all stories fit into a single theme). Aim for between 6 and 8.
4. Categorise the rest of the stories
Now, go through the top stories from each of your sources and quickly sort using the themes / categories you’ve just created (see the first column below).
Be careful to use the same spelling and categories during this whole process as we will be setting up formulas later to count them. You can do this by either using data validation (setting up data entry through drop downs) or using the autocomplete function.
Now the fun part! Pop your themes in the left most column, and use COUNTIF formulas to tally up how many articles of each category you found.
Note: The formula below is just saying “Count the number of times in column A on the Forbes data tab that ‘Implementation’ appears”. Ensuring this works is why we took our time with data integrity earlier. Use the bar chart option under Conditional Formatting to make it easy to eyeball key insights.
So, what have we learnt?? My focus is HR tech and workplace flexibility, and what I found was:
- If we want to appear in Business Press, stories on Implementation and Education (ie, quantifying the benefits) are more likely to get coverage.
- If we want to appear in Consumer Press, then we should pitch articles with a gender or family lens.
- The Specialist Press skews very heavily towards case studies and advocacy type articles.
And how did we use that knowledge?
Since we’re targeting HR buyers to drive sales, we immediately focused on themes that would get us into both business and specialist press.
We invested in a beautiful report featuring case studies of well known clients telling stories of how they implemented workplace change. It wasn’t a cheap piece of content to produce but this research gave us the confidence to commit the resources.
I also picked up an interesting tidbit on who we should reach out to. This shows which authors wrote articles, and how many were specifically about Flex (the topic of interest).
There’s two obvious ones, Tony and Kasey. Tony’s a prolific dude, he’s published 28 articles and 7 (or 25%) are about flex. Pretty good.
However, while Kasey has only published three articles, all of them have been about flex. I’d put ALOT of effort into Kasey :)
As mentioned, this is just the very pointy end of hacking PR. Armed with this data, you still need to come up with angles, work the relationships and get your story out there.
Luckily… I’m working on part 2 of this guide. It’ll include:
- How (and when) to reach out to journalists and maximise the chance they’ll respond.
- How to think about attribution for PR.
I’m a Growth Marketer based in Sydney Australia. I love working with awesome start ups to help them grow into successful businesses.
If you have any questions, or would like to get in touch… well, get in touch!